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I have a point dataset of hundreds of thousands of points (zip+4s), many of which share the same value for one attribute (zip+4), but have different values for other attributes (ex: address). In other words, each zip+4 is represented by multiple points at different addresses. I need a dataset that has only one record for each zip+4. In the past, I have simply dissolved the entire dataset by zip+4 and ended up with multi-point features. This, however is starting to cause problems down the line, because I need the location of each zip+4 to be unique - and if a single zip+4 crosses into multiple cities or counties, it gives me issues.

I have gotten as far as dissolving them into smaller multi-point features by city/county, so that each unique combination of zip+4, city, and county is represented by it's own multi-point feature (and I retained a count attribute of how many points make up each multi-point feature). Now how do I get rid of all but the one record for each zip+4 that has the most points in it?

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Using the Delete Identical tool from the "Data Management" toolbox, you can specify by which fields to compare/delete records.

Or perhaps, Find Identical so you can select different fields and view/choose the correct records to be deleted before taking them away.

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  • I don't think Delete Identical works because I can't say "if the count value is less than the max count value for that zip4, delete it." I don't want to just delete some of them, I want to make sure I'm deleting the right ones. – MMB May 1 '14 at 21:25
  • I think you will need to convert multipoint into point features. Do all of the points/address have the same attribute for zip+4, if so then remove all fields except zip+4, buffer by a very small number & dissolve then use the surviving centroid by feature to point resources.arcgis.com/en/help/main/10.1/index.html#//…. Note: dissolving a very large dataset causes problems (I've seen three posts about it recently) and it may be necessary to Dice resources.arcgis.com/en/help/main/10.1/index.html#//… before doing it. – Michael Stimson May 2 '14 at 3:44

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